DevOps / Cloud Engineer

We are seeking a **Senior DevOps / MLOps / Data Engineer** with strong experience in Azure to lead platform engineering, deployment automation, and AI/ML model deployment. This role focuses on building scalable, secure, and cost\-efficient cloud solutions while enabling end\-to\-end ML lifecycle management and data engineering capabilities. **Key Responsibilities** **DevOps, Deployment \& MLOps (Primary Focus)** * Design and implement CI/CD pipelines using Azure DevOps, Git, and YAML * Manage end\-to\-end deployments across Dev, QA, and Production environments * Lead deployment of AI/ML models into production using automated pipelines * Implement model lifecycle management (training, validation, deployment, monitoring) * Deploy and manage batch and real\-time inference models * Automate infrastructure provisioning using ARM, Bicep, or Terraform * Manage Azure resources via Portal, CLI, and scripting * Oversee Databricks cluster management, scaling, and performance tuning * Implement release strategies, versioning, rollback, and environment configuration * Build scalable API\-based model inference endpoints * Integrate Azure AI services (e.g., Azure AI Search, Azure AI Foundry) * Monitor system reliability, model performance, and drift **Data Engineering** * Design and develop data pipelines using Azure Data Factory, Databricks, and ADLS * Build and optimize data models in Azure SQL, SQL Server, and Oracle * Implement ETL/ELT processes for large\-scale data processing * Ensure data quality, governance, and performance optimization * Support medallion architecture (Bronze, Silver, Gold layers) **Security \& Compliance** * Implement secure cloud architecture using RBAC, Managed Identities, and Key Vault * Secure data pipelines and ML endpoints (encryption, private endpoints, network controls) * Ensure compliance with data protection and governance standards * Manage secrets, credentials, and access policies **Cost Optimization** * Optimize cloud costs across Databricks, storage, and compute resources * Implement cluster right\-sizing and auto\-scaling strategies * Monitor usage and enforce cost governance * Recommend cost\-performance improvements **API \& Integration** * Design and build scalable REST APIs for data access and model inference * Develop API\-based integrations with internal and external systems * Enable real\-time and batch data integrations * Implement API security (authentication, throttling, versioning) * Support event\-driven architectures and messaging systems **Required Qualifications** * 10\+ years of IT experience, including 5\+ years in DevOps / MLOps / Data Engineering * Strong expertise in: + Azure ecosystem (ADF, Databricks, ADLS, Azure SQL) + CI/CD pipelines, Git, and YAML + Infrastructure as Code (ARM, Bicep, Terraform) + SQL and relational databases (Azure SQL, Oracle) + REST API development and integration * Proven experience in: + Deploying AI/ML models into production + End\-to\-end deployment pipelines and release management + Cluster management and optimization **Nice to Have** * Azure AI Search and Azure AI Foundry * Event\-driven architecture (Event Grid, Service Bus) * Streaming platforms (Kafka, Event Hubs) * Containerization (Docker, Kubernetes, AKS) * Experience with LLMs / Generative AI pipelines * Data governance and medallion architecture **Soft Skills** * Strong problem\-solving and troubleshooting skills * Ability to collaborate across DevOps, Data, and ML teams * Excellent communication and documentation * Leadership and mentoring capabilities **Must\-Have Requirements** * 10\+ years designing and implementing CI/CD pipelines (Azure DevOps, Git, YAML) * 10\+ years deploying AI/ML models using automated pipelines * 10\+ years implementing ML lifecycle management * 10\+ years building data pipelines using ADF, Databricks, and ADLS